SynthesisPloS one2024
A meta-analysis of technology-based interventions on treatment adherence and treatment success among TBC patients.
Synthesis in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The role of digital tools in enhancing antiretroviral therapy adherence among adolescents and young adults with HIV: a systematic review of randomized controlled trials.BMC infectious diseases · 2025Pooled it
- Advancing Undergraduate Student Mental Healthcare of Social Anxiety Disorder: Evaluating the Acceptance of AR-Assisted Cognitive Behavioral Therapy Through TAM-Based Constructs.Healthcare (Basel, Switzerland) · 2026Article
- Integrated Artificial Intelligence Framework for Tuberculosis Treatment Abandonment Prediction: A Multi-Paradigm Approach.Journal of clinical medicine · 2025Article
- Technology-integrated nursing interventions to improve adherence to tuberculosis medication: a scoping review.BMC nursing · 2025Article
- Analysis of the epidemiological characteristics of pulmonary tuberculosis in Shijiazhuang, China 2010-2023.Frontiers in public health · 2025Article
- Emerging Research Trends on Medication Adherence in Tuberculosis Treatment: A Bibliometric Study of Research Between 2015 and 2024 to Inform Future Research Trajectory.Patient preference and adherence · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Various technology-based interventions have been designed to improve medication adherence and treatment success. However, research on the most effective mode to address this issue is still limited. Our study evaluated the effectiveness of technology-based interventions in improving treatment adherence, completion, and treatment success among tuberculosis (TBC) patients. We conducted a meta-analysis of randomized controlled trials by searching articles from six databases including PubMed, Science Direct, Cochrane, Jstor, Embase, and Scopus from 2018 to April 2023. Two independent reviewers assessed the study quality using the Cochrane Risk of Bias 2.0 tool. We analysed the data using a random-effects model. We also conducted publication bias and sensitivity analysis. In total, 13 studies were identified and 4,794 participants were included in the meta-analysis. The results indicated that technology-based interventions were effective in improving treatment adherence, completion, and success (Odds Ratio (OR): 2.57, 95% Confident Interval (CI): 1.01-6.50, I2 = 86.6%; OR: 1.77, 95% CI: 0.95-3.28, I2: 82.3%; OR: 1.61, 95% CI: 0.85-3.06, I2: 84%, respectively). We examined the possibility of publication bias in the published studies included in this systematic review. However, no evidence of publication bias was found. From the sensitivity analysis by removing one study randomly, we found that our results are robust. Based on the results, we can conclude that technology-based interventions like MERM, text-based messages, video conferencing, and VOT are effective in increasing treatment adherence and completion in tuberculosis management. Therefore, technology shows immense potential in enhancing patient outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.